Special Virtual Issue: Bayesian Inference for Psychology

In this special issue of Psychonomic Bulletin & Review, we review a different set of methods and principles, now based on the theory of probability and its deterministic sibling, formal logic. The aim of the special issue is to provide and recommend this collection of statistical tools that derives from probability theory: Bayesian statistics. The special section is divided into four sections. The first section is a coordinated five part introduction that starts from the most basic concepts and works up to the general structure of complex problems and to contemporary issues. The second section is a selection of advanced topics covered in-depth by some of the world’s leading experts on statistical inference in psychology. The third section is an extensive collection of teaching resources, reading lists, and strong arguments for the use of Bayesian methods at the expense of classical methods. The final section contains a number of applications of advanced Bayesian analyses that provides an idea of the wide reach of Bayesian methods for psychological science.

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Aims and Scope

The journal provides coverage spanning a broad spectrum of topics in all areas of experimental psychology. The journal is primarily dedicated to the publication of theory and review articles and brief reports of outstanding experimental work. Areas of coverage include cognitive psychology broadly construed, including but not limited to action, perception, & attention, language, learning & memory, reasoning & decision making, and social cognition. We welcome submissions that approach these issues from a variety of perspectives such as behavioral measurements, comparative psychology, development, evolutionary psychology, genetics, neuroscience, and quantitative/computational modeling. We particularly encourage integrative research that crosses traditional content and methodological boundaries.